We present a new algorithm, Robust Automated Assignment of Rigid Rotors (RAARR), for assigning rotational spectra of asymmetric tops. The RAARR algorithm can automatically assign experimental spectra under a broad range of conditions, including spectra comprised of multiple mixture components, in 100 seconds. The RAARR algorithm exploits constraints placed by the conservation of energy to find sets of connected lines in an unassigned spectrum. The highly constrained structure of these sets eliminates all but a handful of plausible assignments for a given set, greatly reducing the number of potential assignments that must be evaluated. We successfully apply our algorithm to automatically assign 15 experimental spectra, including 5 previously unassigned species, without prior estimation of molecular rotational constants. In 9 of the 15 cases, the RAARR algorithm successfully assigns two or more mixture components.
BackgroundMicrowave spectroscopy provides our most accurate measurements of molecular structures. Typical spectra recorded by modern instruments are comprised of thousands of lines, each corresponding to a specific rotational transition of a specific species. Assigning the correct quantum numbers to lines in an observed spectrum is a prerequisite for extracting meaningful structural information about the molecule. Today, such assignments are typically performed using a combination of quantum chemical simulation, which can in most cases predict rotational constants to within a few percent, and often laborious inspection of the observed spectrum. Assignment of complex spectra remains very much an art, and veteran spectroscopists employ diverse tricks as well as deep intuition to find requisite patterns amid congested spectra [1].Robust automatic fitting of rotational spectra or rovibronic spectra has been a longstanding goal of the spectroscopy community. Attempts at fully automated algorithms include genetic algorithms [2], broad searches combined with quantum chemical calculation [3,4], assignment via nonlinear spectroscopy [5,6], and artificial neural networks [7]. Colin Western's PGOPHER program [8] includes an implementation of the automated fitting routine described in reference [3]. Of particular note are the genetic algorithms demonstrated by Meerts and Schmitt, which have successfully assigned rotationally resolved electronic spectra with no need for prior estimation of molecular constants [9,10]. These algorithms furthermore can be applied to a wide range of candidate Hamiltonians, in contrast to the rigid rotor Hamiltonian assumed in this work.Automated, context-free assignment and structure determination from high-dimensional NMR data is now an integral part of modern NMR analysis [11,12]. In many cases approaches to spectral assignment leverage the ability of modern quantum chemical calculations to predict the structure of a compound, and thus the approximate rotational constants, from the elemental composition and connectivity of the compound, vastly reducing the size of the search space. This...